Senior MLOps Engineer - AI Platform & Deployment

Fractal Analytics Inc; New York (NY); On-site; USD 100,000 - 125,000; Full time

Job summary

Fractal Analytics Inc. is hiring a senior MLOps Engineer on a consulting basis to operationalize ML solutions across purchase and underwriting domains.

You will build production-grade inference services, data pipelines, and model lifecycle tooling, working with Data Science and Data Engineering teams. The role is hands-on, focusing on scalable services in a production environment using FastAPI, Docker, Kubernetes, MLflow, and Databricks.

Qualifications

• Strong Python and backend development skills for production systems.
• Hands-on experience with FastAPI and scalable ML platforms.
• Proven track record building end-to-end ML pipelines in Databricks.
• Experience with AWS services and event-driven architectures.
• Familiarity with Docker, Kubernetes, and CI/CD workflows.

Responsibilities

• Build and operate production ML inference services and data pipelines.
• Design scalable model serving and asynchronous architectures.
• Develop and maintain ML platform capabilities and governance.
• Collaborate with Data Science and Data Engineering teams to productionize solutions.

Skills

Python

FastAPI

Databricks

MLflow

Delta Lake

Databricks Workflows

DABs

AWS (SQS, EKS, Aurora PostgreSQL)

Kafka

Docker

Kubernetes

CI/CD (GitHub Actions/Jenkins)

GitHub Copilot

Claude Code

Observability

Communication

Tools

Databricks

Kafka

Docker

Kubernetes

MLflow

GitHub Copilot

Claude Code

GitHub Actions

Jenkins

SQS

Aurora PostgreSQL

Job description

Fractal Analytics Inc. is hiring a senior MLOps Engineer on a consulting basis to operationalize ML solutions across purchase and underwriting domains.

You will build production-grade inference services, data pipelines, and model lifecycle tooling, working with Data Science and Data Engineering teams. The role is hands-on, focusing on scalable services in a production environment using FastAPI, Docker, Kubernetes, MLflow, and Databricks.